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Interpretative Guides For Interacting With Tissue Atlas And Digital Pathology Data Using The Minerva Browser

Rumana Rashid, Y. Chen, John Hoffer, Jeremy L. Muhlich, Jia-Ren Lin, R. Krueger, H. Pfister, R. Mitchell, S. Santagata, P. Sorger
Published 2020 ·

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The recent introduction of highly multiplexed imaging of human tissues and tumors promises to fundamentally advance research in tissue biology and human disease. At the same time, histopathology in the clinical setting is undergoing a rapid transition to digital methods. Thus, repositories of imaging data from research and clinical specimens will soon join genomic databases as a means to systematically explore the molecular basis of disease. Even with recent advances in machine learning, experience in anatomic pathology has shown that there is no substitute for expert visual review, annotation, and description of image data. We review the ecosystem of software available for atlas and histopathology images and introduce a new Web-based software tool, Minerva Story, that addresses a critical unmet need. Minerva is an interpretative and interactive guide to complex images organized around guided analysis. We discuss how Minerva and similar software will be integrated into multi-omic browsers for data dissemination of future atlases.
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